Triple

T27625388
Position Surface form Disambiguated ID Type / Status
Subject Forestville E696188 entity
Predicate hasRecreationFacility P6792 FINISHED
Object Forestville RSL Club
Forestville RSL Club is a community-based Returned and Services League venue in Forestville offering dining, social events, and recreational facilities for members and guests.
E1780127 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Forestville RSL Club | Statement: [Forestville, hasRecreationFacility, Forestville RSL Club]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Forestville RSL Club
Triple: [Forestville, hasRecreationFacility, Forestville RSL Club]
Generated description
Forestville RSL Club is a community-based Returned and Services League venue in Forestville offering dining, social events, and recreational facilities for members and guests.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69ef59092c8881908114ad184248cc46 completed April 27, 2026, 12:39 p.m.
NER Named-entity recognition batch_69f6311f4dc48190a88ba7863642a3e6 completed May 2, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12d0f73a508190b818eaf903620ac7 completed May 24, 2026, 10:20 a.m.
NEDg Description generation batch_6a12d1b7236c819092446204ac71c8b2 completed May 24, 2026, 10:23 a.m.
NED2 Entity disambiguation (via description) batch_6a12d26af1288190a2925d726ab5be31 completed May 24, 2026, 10:26 a.m.
Created at: April 27, 2026, 2:17 p.m.